{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd \n",
    "pd.set_option('display.max_columns', 100)\n",
    "pd.set_option('display.max_rows', 200)\n",
    "import numpy as np \n",
    "from scipy.stats import skew\n",
    "import scipy.stats as stats \n",
    "\n",
    "import seaborn as sns \n",
    "import matplotlib.pyplot as plt "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = pd.read_csv('train.csv')\n",
    "test = pd.read_csv('test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1460, 81)\n",
      "(1459, 80)\n"
     ]
    }
   ],
   "source": [
    "print(train.shape)\n",
    "print(test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>MSZoning</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>Street</th>\n",
       "      <th>Alley</th>\n",
       "      <th>LotShape</th>\n",
       "      <th>LandContour</th>\n",
       "      <th>Utilities</th>\n",
       "      <th>LotConfig</th>\n",
       "      <th>LandSlope</th>\n",
       "      <th>Neighborhood</th>\n",
       "      <th>Condition1</th>\n",
       "      <th>Condition2</th>\n",
       "      <th>BldgType</th>\n",
       "      <th>HouseStyle</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>RoofStyle</th>\n",
       "      <th>RoofMatl</th>\n",
       "      <th>Exterior1st</th>\n",
       "      <th>Exterior2nd</th>\n",
       "      <th>MasVnrType</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>ExterQual</th>\n",
       "      <th>ExterCond</th>\n",
       "      <th>Foundation</th>\n",
       "      <th>BsmtQual</th>\n",
       "      <th>BsmtCond</th>\n",
       "      <th>BsmtExposure</th>\n",
       "      <th>BsmtFinType1</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinType2</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>Heating</th>\n",
       "      <th>HeatingQC</th>\n",
       "      <th>CentralAir</th>\n",
       "      <th>Electrical</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>HalfBath</th>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <th>KitchenQual</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>Functional</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>FireplaceQu</th>\n",
       "      <th>GarageType</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageFinish</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "      <th>GarageQual</th>\n",
       "      <th>GarageCond</th>\n",
       "      <th>PavedDrive</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>PoolQC</th>\n",
       "      <th>Fence</th>\n",
       "      <th>MiscFeature</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SaleType</th>\n",
       "      <th>SaleCondition</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>65.0</td>\n",
       "      <td>8450</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2003</td>\n",
       "      <td>2003</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>196.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>No</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>706.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>856.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>856</td>\n",
       "      <td>854</td>\n",
       "      <td>0</td>\n",
       "      <td>1710</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>8</td>\n",
       "      <td>Typ</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2.0</td>\n",
       "      <td>548.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>61</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>208500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>20</td>\n",
       "      <td>RL</td>\n",
       "      <td>80.0</td>\n",
       "      <td>9600</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Reg</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Veenker</td>\n",
       "      <td>Feedr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>1Story</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
       "      <td>1976</td>\n",
       "      <td>1976</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>MetalSd</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>CBlock</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>978.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>284.0</td>\n",
       "      <td>1262.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1262</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1262</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>1976.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2.0</td>\n",
       "      <td>460.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>298</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>2007</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>181500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>68.0</td>\n",
       "      <td>11250</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Inside</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>CollgCr</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>2001</td>\n",
       "      <td>2002</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>162.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Mn</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>486.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>434.0</td>\n",
       "      <td>920.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>920</td>\n",
       "      <td>866</td>\n",
       "      <td>0</td>\n",
       "      <td>1786</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>6</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>2.0</td>\n",
       "      <td>608.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>42</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>223500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>70</td>\n",
       "      <td>RL</td>\n",
       "      <td>60.0</td>\n",
       "      <td>9550</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>Corner</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>Crawfor</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>7</td>\n",
       "      <td>5</td>\n",
       "      <td>1915</td>\n",
       "      <td>1970</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>Wd Sdng</td>\n",
       "      <td>Wd Shng</td>\n",
       "      <td>None</td>\n",
       "      <td>0.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>BrkTil</td>\n",
       "      <td>TA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>No</td>\n",
       "      <td>ALQ</td>\n",
       "      <td>216.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>540.0</td>\n",
       "      <td>756.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>961</td>\n",
       "      <td>756</td>\n",
       "      <td>0</td>\n",
       "      <td>1717</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>7</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>Detchd</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>3.0</td>\n",
       "      <td>642.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>0</td>\n",
       "      <td>35</td>\n",
       "      <td>272</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2006</td>\n",
       "      <td>WD</td>\n",
       "      <td>Abnorml</td>\n",
       "      <td>140000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>60</td>\n",
       "      <td>RL</td>\n",
       "      <td>84.0</td>\n",
       "      <td>14260</td>\n",
       "      <td>Pave</td>\n",
       "      <td>NaN</td>\n",
       "      <td>IR1</td>\n",
       "      <td>Lvl</td>\n",
       "      <td>AllPub</td>\n",
       "      <td>FR2</td>\n",
       "      <td>Gtl</td>\n",
       "      <td>NoRidge</td>\n",
       "      <td>Norm</td>\n",
       "      <td>Norm</td>\n",
       "      <td>1Fam</td>\n",
       "      <td>2Story</td>\n",
       "      <td>8</td>\n",
       "      <td>5</td>\n",
       "      <td>2000</td>\n",
       "      <td>2000</td>\n",
       "      <td>Gable</td>\n",
       "      <td>CompShg</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>VinylSd</td>\n",
       "      <td>BrkFace</td>\n",
       "      <td>350.0</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>PConc</td>\n",
       "      <td>Gd</td>\n",
       "      <td>TA</td>\n",
       "      <td>Av</td>\n",
       "      <td>GLQ</td>\n",
       "      <td>655.0</td>\n",
       "      <td>Unf</td>\n",
       "      <td>0.0</td>\n",
       "      <td>490.0</td>\n",
       "      <td>1145.0</td>\n",
       "      <td>GasA</td>\n",
       "      <td>Ex</td>\n",
       "      <td>Y</td>\n",
       "      <td>SBrkr</td>\n",
       "      <td>1145</td>\n",
       "      <td>1053</td>\n",
       "      <td>0</td>\n",
       "      <td>2198</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>Gd</td>\n",
       "      <td>9</td>\n",
       "      <td>Typ</td>\n",
       "      <td>1</td>\n",
       "      <td>TA</td>\n",
       "      <td>Attchd</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>RFn</td>\n",
       "      <td>3.0</td>\n",
       "      <td>836.0</td>\n",
       "      <td>TA</td>\n",
       "      <td>TA</td>\n",
       "      <td>Y</td>\n",
       "      <td>192</td>\n",
       "      <td>84</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>2008</td>\n",
       "      <td>WD</td>\n",
       "      <td>Normal</td>\n",
       "      <td>250000.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Id  MSSubClass MSZoning  LotFrontage  LotArea Street Alley LotShape  \\\n",
       "0   1          60       RL         65.0     8450   Pave   NaN      Reg   \n",
       "1   2          20       RL         80.0     9600   Pave   NaN      Reg   \n",
       "2   3          60       RL         68.0    11250   Pave   NaN      IR1   \n",
       "3   4          70       RL         60.0     9550   Pave   NaN      IR1   \n",
       "4   5          60       RL         84.0    14260   Pave   NaN      IR1   \n",
       "\n",
       "  LandContour Utilities LotConfig LandSlope Neighborhood Condition1  \\\n",
       "0         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
       "1         Lvl    AllPub       FR2       Gtl      Veenker      Feedr   \n",
       "2         Lvl    AllPub    Inside       Gtl      CollgCr       Norm   \n",
       "3         Lvl    AllPub    Corner       Gtl      Crawfor       Norm   \n",
       "4         Lvl    AllPub       FR2       Gtl      NoRidge       Norm   \n",
       "\n",
       "  Condition2 BldgType HouseStyle  OverallQual  OverallCond  YearBuilt  \\\n",
       "0       Norm     1Fam     2Story            7            5       2003   \n",
       "1       Norm     1Fam     1Story            6            8       1976   \n",
       "2       Norm     1Fam     2Story            7            5       2001   \n",
       "3       Norm     1Fam     2Story            7            5       1915   \n",
       "4       Norm     1Fam     2Story            8            5       2000   \n",
       "\n",
       "   YearRemodAdd RoofStyle RoofMatl Exterior1st Exterior2nd MasVnrType  \\\n",
       "0          2003     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "1          1976     Gable  CompShg     MetalSd     MetalSd       None   \n",
       "2          2002     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "3          1970     Gable  CompShg     Wd Sdng     Wd Shng       None   \n",
       "4          2000     Gable  CompShg     VinylSd     VinylSd    BrkFace   \n",
       "\n",
       "   MasVnrArea ExterQual ExterCond Foundation BsmtQual BsmtCond BsmtExposure  \\\n",
       "0       196.0        Gd        TA      PConc       Gd       TA           No   \n",
       "1         0.0        TA        TA     CBlock       Gd       TA           Gd   \n",
       "2       162.0        Gd        TA      PConc       Gd       TA           Mn   \n",
       "3         0.0        TA        TA     BrkTil       TA       Gd           No   \n",
       "4       350.0        Gd        TA      PConc       Gd       TA           Av   \n",
       "\n",
       "  BsmtFinType1  BsmtFinSF1 BsmtFinType2  BsmtFinSF2  BsmtUnfSF  TotalBsmtSF  \\\n",
       "0          GLQ       706.0          Unf         0.0      150.0        856.0   \n",
       "1          ALQ       978.0          Unf         0.0      284.0       1262.0   \n",
       "2          GLQ       486.0          Unf         0.0      434.0        920.0   \n",
       "3          ALQ       216.0          Unf         0.0      540.0        756.0   \n",
       "4          GLQ       655.0          Unf         0.0      490.0       1145.0   \n",
       "\n",
       "  Heating HeatingQC CentralAir Electrical  1stFlrSF  2ndFlrSF  LowQualFinSF  \\\n",
       "0    GasA        Ex          Y      SBrkr       856       854             0   \n",
       "1    GasA        Ex          Y      SBrkr      1262         0             0   \n",
       "2    GasA        Ex          Y      SBrkr       920       866             0   \n",
       "3    GasA        Gd          Y      SBrkr       961       756             0   \n",
       "4    GasA        Ex          Y      SBrkr      1145      1053             0   \n",
       "\n",
       "   GrLivArea  BsmtFullBath  BsmtHalfBath  FullBath  HalfBath  BedroomAbvGr  \\\n",
       "0       1710           1.0           0.0         2         1             3   \n",
       "1       1262           0.0           1.0         2         0             3   \n",
       "2       1786           1.0           0.0         2         1             3   \n",
       "3       1717           1.0           0.0         1         0             3   \n",
       "4       2198           1.0           0.0         2         1             4   \n",
       "\n",
       "   KitchenAbvGr KitchenQual  TotRmsAbvGrd Functional  Fireplaces FireplaceQu  \\\n",
       "0             1          Gd             8        Typ           0         NaN   \n",
       "1             1          TA             6        Typ           1          TA   \n",
       "2             1          Gd             6        Typ           1          TA   \n",
       "3             1          Gd             7        Typ           1          Gd   \n",
       "4             1          Gd             9        Typ           1          TA   \n",
       "\n",
       "  GarageType  GarageYrBlt GarageFinish  GarageCars  GarageArea GarageQual  \\\n",
       "0     Attchd       2003.0          RFn         2.0       548.0         TA   \n",
       "1     Attchd       1976.0          RFn         2.0       460.0         TA   \n",
       "2     Attchd       2001.0          RFn         2.0       608.0         TA   \n",
       "3     Detchd       1998.0          Unf         3.0       642.0         TA   \n",
       "4     Attchd       2000.0          RFn         3.0       836.0         TA   \n",
       "\n",
       "  GarageCond PavedDrive  WoodDeckSF  OpenPorchSF  EnclosedPorch  3SsnPorch  \\\n",
       "0         TA          Y           0           61              0          0   \n",
       "1         TA          Y         298            0              0          0   \n",
       "2         TA          Y           0           42              0          0   \n",
       "3         TA          Y           0           35            272          0   \n",
       "4         TA          Y         192           84              0          0   \n",
       "\n",
       "   ScreenPorch  PoolArea PoolQC Fence MiscFeature  MiscVal  MoSold  YrSold  \\\n",
       "0            0         0    NaN   NaN         NaN        0       2    2008   \n",
       "1            0         0    NaN   NaN         NaN        0       5    2007   \n",
       "2            0         0    NaN   NaN         NaN        0       9    2008   \n",
       "3            0         0    NaN   NaN         NaN        0       2    2006   \n",
       "4            0         0    NaN   NaN         NaN        0      12    2008   \n",
       "\n",
       "  SaleType SaleCondition  SalePrice  \n",
       "0       WD        Normal   208500.0  \n",
       "1       WD        Normal   181500.0  \n",
       "2       WD        Normal   223500.0  \n",
       "3       WD       Abnorml   140000.0  \n",
       "4       WD        Normal   250000.0  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.concat(objs=[train, test], axis=0, sort=False, ignore_index=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Id</th>\n",
       "      <th>MSSubClass</th>\n",
       "      <th>LotFrontage</th>\n",
       "      <th>LotArea</th>\n",
       "      <th>OverallQual</th>\n",
       "      <th>OverallCond</th>\n",
       "      <th>YearBuilt</th>\n",
       "      <th>YearRemodAdd</th>\n",
       "      <th>MasVnrArea</th>\n",
       "      <th>BsmtFinSF1</th>\n",
       "      <th>BsmtFinSF2</th>\n",
       "      <th>BsmtUnfSF</th>\n",
       "      <th>TotalBsmtSF</th>\n",
       "      <th>1stFlrSF</th>\n",
       "      <th>2ndFlrSF</th>\n",
       "      <th>LowQualFinSF</th>\n",
       "      <th>GrLivArea</th>\n",
       "      <th>BsmtFullBath</th>\n",
       "      <th>BsmtHalfBath</th>\n",
       "      <th>FullBath</th>\n",
       "      <th>HalfBath</th>\n",
       "      <th>BedroomAbvGr</th>\n",
       "      <th>KitchenAbvGr</th>\n",
       "      <th>TotRmsAbvGrd</th>\n",
       "      <th>Fireplaces</th>\n",
       "      <th>GarageYrBlt</th>\n",
       "      <th>GarageCars</th>\n",
       "      <th>GarageArea</th>\n",
       "      <th>WoodDeckSF</th>\n",
       "      <th>OpenPorchSF</th>\n",
       "      <th>EnclosedPorch</th>\n",
       "      <th>3SsnPorch</th>\n",
       "      <th>ScreenPorch</th>\n",
       "      <th>PoolArea</th>\n",
       "      <th>MiscVal</th>\n",
       "      <th>MoSold</th>\n",
       "      <th>YrSold</th>\n",
       "      <th>SalePrice</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2433.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2896.000000</td>\n",
       "      <td>2918.000000</td>\n",
       "      <td>2918.000000</td>\n",
       "      <td>2918.000000</td>\n",
       "      <td>2918.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2917.000000</td>\n",
       "      <td>2917.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2760.000000</td>\n",
       "      <td>2918.000000</td>\n",
       "      <td>2918.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>2919.000000</td>\n",
       "      <td>1460.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1460.000000</td>\n",
       "      <td>57.137718</td>\n",
       "      <td>69.305795</td>\n",
       "      <td>10168.114080</td>\n",
       "      <td>6.089072</td>\n",
       "      <td>5.564577</td>\n",
       "      <td>1971.312778</td>\n",
       "      <td>1984.264474</td>\n",
       "      <td>102.201312</td>\n",
       "      <td>441.423235</td>\n",
       "      <td>49.582248</td>\n",
       "      <td>560.772104</td>\n",
       "      <td>1051.777587</td>\n",
       "      <td>1159.581706</td>\n",
       "      <td>336.483727</td>\n",
       "      <td>4.694416</td>\n",
       "      <td>1500.759849</td>\n",
       "      <td>0.429894</td>\n",
       "      <td>0.061364</td>\n",
       "      <td>1.568003</td>\n",
       "      <td>0.380267</td>\n",
       "      <td>2.860226</td>\n",
       "      <td>1.044536</td>\n",
       "      <td>6.451524</td>\n",
       "      <td>0.597122</td>\n",
       "      <td>1978.113406</td>\n",
       "      <td>1.766621</td>\n",
       "      <td>472.874572</td>\n",
       "      <td>93.709832</td>\n",
       "      <td>47.486811</td>\n",
       "      <td>23.098321</td>\n",
       "      <td>2.602261</td>\n",
       "      <td>16.062350</td>\n",
       "      <td>2.251799</td>\n",
       "      <td>50.825968</td>\n",
       "      <td>6.213087</td>\n",
       "      <td>2007.792737</td>\n",
       "      <td>180921.195890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>842.787043</td>\n",
       "      <td>42.517628</td>\n",
       "      <td>23.344905</td>\n",
       "      <td>7886.996359</td>\n",
       "      <td>1.409947</td>\n",
       "      <td>1.113131</td>\n",
       "      <td>30.291442</td>\n",
       "      <td>20.894344</td>\n",
       "      <td>179.334253</td>\n",
       "      <td>455.610826</td>\n",
       "      <td>169.205611</td>\n",
       "      <td>439.543659</td>\n",
       "      <td>440.766258</td>\n",
       "      <td>392.362079</td>\n",
       "      <td>428.701456</td>\n",
       "      <td>46.396825</td>\n",
       "      <td>506.051045</td>\n",
       "      <td>0.524736</td>\n",
       "      <td>0.245687</td>\n",
       "      <td>0.552969</td>\n",
       "      <td>0.502872</td>\n",
       "      <td>0.822693</td>\n",
       "      <td>0.214462</td>\n",
       "      <td>1.569379</td>\n",
       "      <td>0.646129</td>\n",
       "      <td>25.574285</td>\n",
       "      <td>0.761624</td>\n",
       "      <td>215.394815</td>\n",
       "      <td>126.526589</td>\n",
       "      <td>67.575493</td>\n",
       "      <td>64.244246</td>\n",
       "      <td>25.188169</td>\n",
       "      <td>56.184365</td>\n",
       "      <td>35.663946</td>\n",
       "      <td>567.402211</td>\n",
       "      <td>2.714762</td>\n",
       "      <td>1.314964</td>\n",
       "      <td>79442.502883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>1300.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1872.000000</td>\n",
       "      <td>1950.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>334.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>334.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1895.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2006.000000</td>\n",
       "      <td>34900.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>730.500000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>59.000000</td>\n",
       "      <td>7478.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1953.500000</td>\n",
       "      <td>1965.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>220.000000</td>\n",
       "      <td>793.000000</td>\n",
       "      <td>876.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1126.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1960.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>320.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2007.000000</td>\n",
       "      <td>129975.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1460.000000</td>\n",
       "      <td>50.000000</td>\n",
       "      <td>68.000000</td>\n",
       "      <td>9453.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1973.000000</td>\n",
       "      <td>1993.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>368.500000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>467.000000</td>\n",
       "      <td>989.500000</td>\n",
       "      <td>1082.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1444.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1979.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>480.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>26.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2008.000000</td>\n",
       "      <td>163000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>2189.500000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>11570.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>6.000000</td>\n",
       "      <td>2001.000000</td>\n",
       "      <td>2004.000000</td>\n",
       "      <td>164.000000</td>\n",
       "      <td>733.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>805.500000</td>\n",
       "      <td>1302.000000</td>\n",
       "      <td>1387.500000</td>\n",
       "      <td>704.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1743.500000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>7.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>2002.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>576.000000</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>70.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>2009.000000</td>\n",
       "      <td>214000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>2919.000000</td>\n",
       "      <td>190.000000</td>\n",
       "      <td>313.000000</td>\n",
       "      <td>215245.000000</td>\n",
       "      <td>10.000000</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>1600.000000</td>\n",
       "      <td>5644.000000</td>\n",
       "      <td>1526.000000</td>\n",
       "      <td>2336.000000</td>\n",
       "      <td>6110.000000</td>\n",
       "      <td>5095.000000</td>\n",
       "      <td>2065.000000</td>\n",
       "      <td>1064.000000</td>\n",
       "      <td>5642.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>3.000000</td>\n",
       "      <td>15.000000</td>\n",
       "      <td>4.000000</td>\n",
       "      <td>2207.000000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>1488.000000</td>\n",
       "      <td>1424.000000</td>\n",
       "      <td>742.000000</td>\n",
       "      <td>1012.000000</td>\n",
       "      <td>508.000000</td>\n",
       "      <td>576.000000</td>\n",
       "      <td>800.000000</td>\n",
       "      <td>17000.000000</td>\n",
       "      <td>12.000000</td>\n",
       "      <td>2010.000000</td>\n",
       "      <td>755000.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                Id   MSSubClass  LotFrontage        LotArea  OverallQual  \\\n",
       "count  2919.000000  2919.000000  2433.000000    2919.000000  2919.000000   \n",
       "mean   1460.000000    57.137718    69.305795   10168.114080     6.089072   \n",
       "std     842.787043    42.517628    23.344905    7886.996359     1.409947   \n",
       "min       1.000000    20.000000    21.000000    1300.000000     1.000000   \n",
       "25%     730.500000    20.000000    59.000000    7478.000000     5.000000   \n",
       "50%    1460.000000    50.000000    68.000000    9453.000000     6.000000   \n",
       "75%    2189.500000    70.000000    80.000000   11570.000000     7.000000   \n",
       "max    2919.000000   190.000000   313.000000  215245.000000    10.000000   \n",
       "\n",
       "       OverallCond    YearBuilt  YearRemodAdd   MasVnrArea   BsmtFinSF1  \\\n",
       "count  2919.000000  2919.000000   2919.000000  2896.000000  2918.000000   \n",
       "mean      5.564577  1971.312778   1984.264474   102.201312   441.423235   \n",
       "std       1.113131    30.291442     20.894344   179.334253   455.610826   \n",
       "min       1.000000  1872.000000   1950.000000     0.000000     0.000000   \n",
       "25%       5.000000  1953.500000   1965.000000     0.000000     0.000000   \n",
       "50%       5.000000  1973.000000   1993.000000     0.000000   368.500000   \n",
       "75%       6.000000  2001.000000   2004.000000   164.000000   733.000000   \n",
       "max       9.000000  2010.000000   2010.000000  1600.000000  5644.000000   \n",
       "\n",
       "        BsmtFinSF2    BsmtUnfSF  TotalBsmtSF     1stFlrSF     2ndFlrSF  \\\n",
       "count  2918.000000  2918.000000  2918.000000  2919.000000  2919.000000   \n",
       "mean     49.582248   560.772104  1051.777587  1159.581706   336.483727   \n",
       "std     169.205611   439.543659   440.766258   392.362079   428.701456   \n",
       "min       0.000000     0.000000     0.000000   334.000000     0.000000   \n",
       "25%       0.000000   220.000000   793.000000   876.000000     0.000000   \n",
       "50%       0.000000   467.000000   989.500000  1082.000000     0.000000   \n",
       "75%       0.000000   805.500000  1302.000000  1387.500000   704.000000   \n",
       "max    1526.000000  2336.000000  6110.000000  5095.000000  2065.000000   \n",
       "\n",
       "       LowQualFinSF    GrLivArea  BsmtFullBath  BsmtHalfBath     FullBath  \\\n",
       "count   2919.000000  2919.000000   2917.000000   2917.000000  2919.000000   \n",
       "mean       4.694416  1500.759849      0.429894      0.061364     1.568003   \n",
       "std       46.396825   506.051045      0.524736      0.245687     0.552969   \n",
       "min        0.000000   334.000000      0.000000      0.000000     0.000000   \n",
       "25%        0.000000  1126.000000      0.000000      0.000000     1.000000   \n",
       "50%        0.000000  1444.000000      0.000000      0.000000     2.000000   \n",
       "75%        0.000000  1743.500000      1.000000      0.000000     2.000000   \n",
       "max     1064.000000  5642.000000      3.000000      2.000000     4.000000   \n",
       "\n",
       "          HalfBath  BedroomAbvGr  KitchenAbvGr  TotRmsAbvGrd   Fireplaces  \\\n",
       "count  2919.000000   2919.000000   2919.000000   2919.000000  2919.000000   \n",
       "mean      0.380267      2.860226      1.044536      6.451524     0.597122   \n",
       "std       0.502872      0.822693      0.214462      1.569379     0.646129   \n",
       "min       0.000000      0.000000      0.000000      2.000000     0.000000   \n",
       "25%       0.000000      2.000000      1.000000      5.000000     0.000000   \n",
       "50%       0.000000      3.000000      1.000000      6.000000     1.000000   \n",
       "75%       1.000000      3.000000      1.000000      7.000000     1.000000   \n",
       "max       2.000000      8.000000      3.000000     15.000000     4.000000   \n",
       "\n",
       "       GarageYrBlt   GarageCars   GarageArea   WoodDeckSF  OpenPorchSF  \\\n",
       "count  2760.000000  2918.000000  2918.000000  2919.000000  2919.000000   \n",
       "mean   1978.113406     1.766621   472.874572    93.709832    47.486811   \n",
       "std      25.574285     0.761624   215.394815   126.526589    67.575493   \n",
       "min    1895.000000     0.000000     0.000000     0.000000     0.000000   \n",
       "25%    1960.000000     1.000000   320.000000     0.000000     0.000000   \n",
       "50%    1979.000000     2.000000   480.000000     0.000000    26.000000   \n",
       "75%    2002.000000     2.000000   576.000000   168.000000    70.000000   \n",
       "max    2207.000000     5.000000  1488.000000  1424.000000   742.000000   \n",
       "\n",
       "       EnclosedPorch    3SsnPorch  ScreenPorch     PoolArea       MiscVal  \\\n",
       "count    2919.000000  2919.000000  2919.000000  2919.000000   2919.000000   \n",
       "mean       23.098321     2.602261    16.062350     2.251799     50.825968   \n",
       "std        64.244246    25.188169    56.184365    35.663946    567.402211   \n",
       "min         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "25%         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "50%         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "75%         0.000000     0.000000     0.000000     0.000000      0.000000   \n",
       "max      1012.000000   508.000000   576.000000   800.000000  17000.000000   \n",
       "\n",
       "            MoSold       YrSold      SalePrice  \n",
       "count  2919.000000  2919.000000    1460.000000  \n",
       "mean      6.213087  2007.792737  180921.195890  \n",
       "std       2.714762     1.314964   79442.502883  \n",
       "min       1.000000  2006.000000   34900.000000  \n",
       "25%       4.000000  2007.000000  129975.000000  \n",
       "50%       6.000000  2008.000000  163000.000000  \n",
       "75%       8.000000  2009.000000  214000.000000  \n",
       "max      12.000000  2010.000000  755000.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将nan值统一填充为 np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df.fillna(np.nan)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## MSZoning 根据Neighborhood 填充缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "index = df.MSZoning[df.MSZoning.isnull()==True].index\n",
    "\n",
    "df.loc[index[:3], 'MSZoning'] = 'IDOTRR'\n",
    "df.loc[index[3:], 'MSZoning'] = 'Mitchel'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 将 YearBuilt, YearRemodAdd, GarageYrAdd, YrSold, MssubClass 类型转为 object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['YearBuilt'] = df['YearBuilt'].apply(str)\n",
    "df['YearRemodAdd'] = df['YearRemodAdd'].apply(str)\n",
    "df['GarageYrBlt'] = df['GarageYrBlt'].apply(str)\n",
    "df['YrSold'] = df['YrSold'].apply(str)\n",
    "df['MSSubClass'] = df['MSSubClass'].apply(str)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Id', 'LotFrontage', 'LotArea', 'OverallQual', 'OverallCond',\n",
       "       'MasVnrArea', 'BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF', 'TotalBsmtSF',\n",
       "       '1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea', 'BsmtFullBath',\n",
       "       'BsmtHalfBath', 'FullBath', 'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr',\n",
       "       'TotRmsAbvGrd', 'Fireplaces', 'GarageCars', 'GarageArea', 'WoodDeckSF',\n",
       "       'OpenPorchSF', 'EnclosedPorch', '3SsnPorch', 'ScreenPorch', 'PoolArea',\n",
       "       'MiscVal', 'MoSold', 'SalePrice'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_cols = df.dtypes[df.dtypes != 'object'].index\n",
    "obj_cols = df.dtypes[df.dtypes == 'object'].index\n",
    "num_cols"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## GrLivArea 去除 4500 以上的两个离群点"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['GrLivArea'].skew()\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(1,1,1)\n",
    "stats.probplot(df['GrLivArea'].apply(np.log1p), plot=ax)\n",
    "df['GrLivArea'] = df['GrLivArea'].apply(np.log1p)\n",
    "\n",
    "df.drop(train['GrLivArea'][train['GrLivArea']>4500].index, axis=0, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23615aa00b8>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(12,4))\n",
    "ax1 = fig.add_subplot(1,2,1)\n",
    "sns.regplot(df['GrLivArea'], df['SalePrice'])\n",
    "ax2 = fig.add_subplot(1,2,2)\n",
    "sns.scatterplot(df['GrLivArea'], df['SalePrice'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 画出与 SalePrice 相关系数较高的前几个特征与 SalePrice 的散点分布图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x23615b43438>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 900x900 with 30 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.pairplot(df[:len(train)].loc[:,['SalePrice', 'OverallQual', 'GrLivArea', 'GarageArea', 'TotalBsmtSF']].fillna(0))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 缺失值处理"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 缺失值个数 <=10 \n",
    "df['SaleType'].fillna('WD', inplace=True)\n",
    "df['Electrical'].fillna('SBrkr', inplace=True)\n",
    "\n",
    "df['GarageArea'].fillna(df['GarageArea'].mean(), inplace=True)\n",
    "df['GarageCars'].fillna(df['GarageCars'].mean(), inplace=True)\n",
    "df['Exterior1st'].fillna('VinylSd', inplace=True)\n",
    "df['Exterior2nd'].fillna('VinylSd', inplace=True)\n",
    "df['KitchenQual'].fillna(df['KitchenQual'].mode()[0], inplace=True)\n",
    "\n",
    "df['TotalBsmtSF'].fillna(0, inplace=True)\n",
    "df['BsmtFinSF1'].fillna(0, inplace=True)\n",
    "df['BsmtUnfSF'].fillna(0, inplace=True)\n",
    "df['BsmtFinSF2'].fillna(0, inplace=True)\n",
    "\n",
    "df['Functional'].fillna(df['Functional'].mode()[0], inplace=True)\n",
    "df['BsmtHalfBath'].fillna(df['BsmtHalfBath'].mode()[0], inplace=True)\n",
    "df['BsmtFullBath'].fillna(df['BsmtFullBath'].mode()[0], inplace=True)\n",
    "# df['NumOfBath'].fillna(df['NumOfBath'].mode()[0], inplace=True)\n",
    "df['Utilities'].fillna(df['Utilities'].mode()[0], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 缺失值个数 >= 10\n",
    "features = ['MasVnrType', 'BsmtFinType1', 'BsmtFinType2', 'BsmtQual', 'BsmtCond','BsmtExposure',\\\n",
    "    'GarageType', 'GarageCond', 'GarageQual','GarageFinish', 'FireplaceQu',\\\n",
    "    'Fence', 'Alley', 'MiscFeature', 'PoolQC']\n",
    "\n",
    "for feature in features:\n",
    "    df[feature].fillna('None', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['LotFrontage'].fillna(df['LotFrontage'].mean(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['MasVnrArea'].fillna(df['MasVnrArea'].mean(), inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalePrice    1459\n",
       "dtype: int64"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()[df.isnull().sum()!=0].sort_values()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalePrice        1.000000\n",
       "OverallQual      0.795774\n",
       "GrLivArea        0.702933\n",
       "TotalBsmtSF      0.651153\n",
       "GarageCars       0.641047\n",
       "1stFlrSF         0.631530\n",
       "GarageArea       0.629217\n",
       "FullBath         0.562165\n",
       "TotRmsAbvGrd     0.537769\n",
       "MasVnrArea       0.480421\n",
       "Fireplaces       0.469862\n",
       "BsmtFinSF1       0.409384\n",
       "LotFrontage      0.352716\n",
       "WoodDeckSF       0.324758\n",
       "OpenPorchSF      0.321142\n",
       "2ndFlrSF         0.320532\n",
       "HalfBath         0.284590\n",
       "LotArea          0.268179\n",
       "BsmtFullBath     0.228459\n",
       "BsmtUnfSF        0.214460\n",
       "BedroomAbvGr     0.168245\n",
       "ScreenPorch      0.111415\n",
       "PoolArea         0.099490\n",
       "MoSold           0.046124\n",
       "3SsnPorch        0.044568\n",
       "BsmtFinSF2      -0.011422\n",
       "BsmtHalfBath    -0.016881\n",
       "MiscVal         -0.021203\n",
       "Id              -0.021673\n",
       "LowQualFinSF    -0.025625\n",
       "OverallCond     -0.077948\n",
       "EnclosedPorch   -0.128646\n",
       "KitchenAbvGr    -0.135946\n",
       "Name: SalePrice, dtype: float64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr()['SalePrice'].sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## OverallQual"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x236163f5f98>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sns.scatterplot(df['LotFrontage'].fillna(0), df['SalePrice'])\n",
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot()\n",
    "sns.scatterplot(df['OverallQual'], df['SalePrice'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23616acde80>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_subplot(1,1,1)\n",
    "sns.barplot(df['GarageCars'], df['SalePrice'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.21890159885169574"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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JwkyYanfAW+zOKJyV9KyfwpjRsURhJkzlqXbmZKWSkRKbm+1mZqaS7PVQY/0UxoyKJQozITp7+6lp6mTBjOhOKx6KR4TCnDTq7IzCmFGxRGEmREV1M35V5scwUYDTT1Hf2m0r3hkzCpYozIR461AjPo9QmpcR0ziKctPwq1JvK94ZEzZLFGZCvF3ZSEleOkne2P6TKzo7QtsShTHhskRhou7UmW7ePXGGBTNiP3VGZloSWWlJdueTMaNgicJE3YbKJgAWFMS2f2JAUU4atTbluDFhCytRiMh1InJARCpF5J4hXk8Rkafd1ytEpDTotXvd8gMicm1Q+WMickpE9gxq65sickxEdriP68d+eCYSTp3ppqVz7IPU/nSokez0JGZnT+z8TsMpyk2npbOPM919sQ7FmElhxEQhIl7gh8BHgcXALSKyeFC1O4AWVV0APADc7+67GFgLLAGuAx5y2wP4mVs2lAdUdan7eHF0h2QixR9Q3jxwin9/9RAPvnaIylPto25DVXm7spFL5+dP+PxOwxkY8Fdr4ymMCUs4I59WAJWqehhARNYBa4B9QXXWAN90t58FfiAi4pavU9UeoFpEKt32NqrqH4PPPKai4abRvnVl8QRHMnr1bV18+ekdvHO4mfPnZNLQ3sPPNlRz49JCyktzw26nqqGdE6e7+eDCfOJliqU52Wl4Raixy0/GhCWcRFEI1AY9rwNWDldHVftFpA3Ic8vfGbRvYRjvebeIfA7YAvy9qraEsY8Zh+CkFlDlgZcPcqa7n5suLuTi4hx6+gM8uamG57cfo72nP+xk9/K+UwB8cEE+fzrUGJXYRyvJ62F2dqp1aBsTpnD6KIa6XjD4b8Ph6oSz72APA/OBpUA98K9DBiVyp4hsEZEtDQ0NIzRpRqOqoZ2mjl5uXFbI8pJcRITUJC+3ry7lwrlZvLzvJNtqRs7dff4AP994hNXz8mI2EeBwinLTqWvppN8G3hkzonASRR1QFPR8LnB8uDoi4gOygOYw930PVT2pqn5VDQA/xrlUNVS9R1S1XFXLCwoKwjgME66tR1tIS/KyZE7me8q9HuHGpYVkpiXxP57dRU9/6GVFX9xdT31bN3/1obJohjsmxTnp9PmVd0+ciXUoxsS9cC49bQYWikgZcAync/rWQXXWA7cDG4GbgddUVUVkPfCkiHwPmAMsBDaFejMRma2q9e7TTwJ7QtU3kdXZ28++46cpL80dcnBcapKXTy4r5GcbjvDgq5V89dpzhmxHVfnJn6qZV5DBFefMiHbYwPB9QkMZ6NDeXtvK+YVZ0QrJmClhxDMKVe0H7gZeAvYDz6jqXhH5lojc4FZ7FMhzO6u/Atzj7rsXeAan4/sPwF2q6gcQkadwEss5IlInIne4bX1HRHaLyC7gCuDLETpWE4Ydta30B5Tykpxh6yyaOZ2bLp7Lw29WsedY25B1NlU3s/tYG3d8sAyPJz7udgqWnZ7EtBQf249a95cxIwlrvmf3FtUXB5V9I2i7G/jUMPveB9w3RPktw9S/LZyYTHRsPdrCnOxU5mSnhaz3jx8/jzcPNvClp3fwzF+vJjcj+T2v/+StanLSk/gvy+ZGM9wxExGKc9PZXtsa61CMiXs2Mtucday1i/q2bspLRr79NTs9mX+/ZSm1zZ3c+uN3aAlaNa6qoZ1X9p/ktlUlpCV7Q7QSW0W56VQ3dtiKd8aMwBKFOWvLkWZ8HuGiudlh1b9kfj4/ub2cw40d3PqTCvYca+Nbv9nHDQ++RYrPw2dXl0Q54vEZ6KfYUWuXn4wJxRKFAZyxE7vq2lg8J3NUZwEfWljAjz9XTlVDOx9/8C1+vvEI1yyZxa/vupQZ0+Njyo7hFGan4fUI247a5SdjQonNmpQm7pxo66arz8+5s0Y/w+uHFxXw+OdX8M7hJtauKGJ2Vuj+jXiR7PNw7qzpbLczCmNCskRhADjS1AEw5oWFVs/PY/X8vEiGNCEuLs7h+W11+AOKNw7vzjImHtilJwNAdWMH2elJZKcnj1x5CikvzaGj18/++tOxDsWYuGWJwqCqHGnsoCzGy5TGwgfcCQ43VTfHOBJj4pclCkNVQwcdvX5K8xMvUczJTqMoN42K6qZYh2JM3LJEYdh8xPlrOhHPKABWluWxqboZjZd50I2JM5YoDJuqm5mW4iNvWmL1TwxYUZZLS2cfh8awMJMxicAShWFTdTOleelInKxAN9FWlTl3a1VYP4UxQ7JEkeDqWjo51tqVkP0TA4py05iVmWod2sYMwxJFgjvbP5HAiUJEWFGWS8XhJuunMGYINuAuwQxes+FX2+tITfIwMzO+p9uItpXzclm/8zhHmzoT+uzKmKHYGUWCq27spDQvA0+C9k8MWFnmjKew22SNeT9LFAmss6efxvYeShL0tthg8wumkZeRbB3axgzBEkUCO9bWBTizqCa6gX4K69A25v0sUSSw4y2WKIKtKMulrqWL2ubOWIdiTFyxRJHAjrV2kZuRHNer0E2kyxYVAPDGwYYYR2JMfLFEkcCOtXaNuDZ2IpmXn0FRbhpvHjgV61CMiSuWKBJUZ28/LZ19dtkpiIhwxTkzeLuyiZ5+f6zDMSZuWKJIUMdbuwHrnxjs8nMK6OrzW6e2MUEsUSSoY61OR/ac7MQeaDfY6nn5JPs8vHHA+imMGWCJIkEda+0iJz2J9GQbnB8sLdnLqnl5vGH9FMacZd8SCep4a5ddduL9U5oATE/xUdXQQW1zJ0W56TGIypj4EtYZhYhcJyIHRKRSRO4Z4vUUEXnafb1CREqDXrvXLT8gItcGlT8mIqdEZM+gtnJF5GUROeT+zBn74ZmhdPX6ae7otUQxjHNmTgewswpjXCMmChHxAj8EPgosBm4RkcWDqt0BtKjqAuAB4H5338XAWmAJcB3wkNsewM/cssHuAV5V1YXAq+5zE0Fn+ydyLFEMJW9aMiV56bxu/RTGAOGdUawAKlX1sKr2AuuANYPqrAEed7efBa4SZxWcNcA6Ve1R1Wqg0m0PVf0jMNStJcFtPQ7cOIrjMWE47iaKwixLFEMRES5fVMCGqka6++w2WWPC6aMoBGqDntcBK4ero6r9ItIG5Lnl7wzat3CE95upqvVuW/UiMiOMGM0onO3ITrEuquGICN19Ae773X7Om515tvzWlcUxjMqY2AjnjGKo+acHr+4yXJ1w9h0TEblTRLaIyJaGBrtEMBo2Intk8woySEvysvtYW6xDMSbmwvmTsg4oCno+Fzg+TJ06EfEBWTiXlcLZd7CTIjLbPZuYDQzZo6iqjwCPAJSXl9uyZGEa6MguLxnfPQJD3S00YCr81e3zeDi/MJOddW309gdI9tmd5CZxhfOvfzOwUETKRCQZp3N6/aA664Hb3e2bgdfUWVNyPbDWvSuqDFgIbBrh/YLbuh14IYwYTZiOtw0MtLMzipFcODeb3v4AB06eiXUoxsTUiIlCVfuBu4GXgP3AM6q6V0S+JSI3uNUeBfJEpBL4Cu6dSqq6F3gG2Af8AbhLVf0AIvIUsBE4R0TqROQOt61vA1eLyCHgave5iZDjrZYowlWWn8G0FB+76lpjHYoxMRVWb6aqvgi8OKjsG0Hb3cCnhtn3PuC+IcpvGaZ+E3BVOHGZ0atv6yYz1cc068gekUeE8wuz2HKkme4+P6lJNh27SUx24TXBWEf26Fw0N4v+gLK//nSsQzEmZuzPygTS2dtP45keLijMiur7hOronmyKctPJSkti97E2lhXbJAEmMdkZRQLZX38GBebYQLuweUS4sDCLQyfb6eztj3U4xsSEJYoEsu+4MybAphYfnYuKsvGrsrPWOrVNYrJEkUD2HDtNerKXrLSkWIcyqczJTqMwO42K6macu76NSSyWKBLInuNtzMlOw5mGy4zGyrJcTp3pYfORlliHYsyEs0SRIHr7Axw8ecb6J8bowrnZpCZ5eKLiaKxDMWbCWaJIEAdPnqHPr9Y/MUbJPg/LinP4/e4TNLX3xDocYyaUJYoEse+4Mw7AxlCM3YrSXHr9AZ7ZUhfrUIyZUJYoEsSe421MS/GRm5Ec61AmrZmZqawsy+XJTUcJBKxT2yQOSxQJYs+xNhbPzsRjHdnj8tlVJdQ2d/HGQVsm1SQOSxQJwB9Q9tefYUlh5siVTUjXLplFYXYaD75WabfKmoRhiSIBHG5op6vPz5I50Z26IxEk+zz87RXz2V7TyluVjbEOx5gJYYkiAeysc0ZkLy2yRBEJNy+fy+ysVL7/yiE7qzAJwRJFAthR28K0FB/z8qfFOpQpIcXn5W8un8+Woy1srGqKdTjGRJ0ligSws7aNC+dm4fFYR3ak/EV5ETMzU/j+q4diHYoxUWeJYorr7vOzv/40S4uyYx3KlJKa5OULH55PRXUzG6yvwkxxliimuL3HT9MfUC6yRBFxt6wopjA7jX98YQ89/f5Yh2NM1FiimOJ2uFNjL7NEEXGpSV7+5ZPnU9XQwUOvV8U6HGOixhLFFLeztpXZWanMyLQ5nqLhinNmcMNFc3jojUoOnTwT63CMiQpLFFPcjtpW65+Ism98YjEZKT7ueX63Te1hpiRLFFNYc0cvNc2d1j8RZfnTUvj69eex9WgL//HHw7EOx5iIs0QxhQ0s3WlnFNF38/K5fOyC2dz/h3d5dqvNLmumFl+sAzDRs6O2FY/ABYU2IjvaRITvffoi2rr6+Npzu8hM9XHNklmxDsuYiLAziilsZ10rC2dMJyPF/h6YCCk+L/9x23LOL8zi7qe288q+k7EOyZiICCtRiMh1InJARCpF5J4hXk8Rkafd1ytEpDTotXvd8gMicu1IbYrIz0SkWkR2uI+l4zvExKSq7LSO7AmXkeLjZ3/5AeYXTOOvfr6Fv1u3ncZRroj3ZEXNkA9jYmXEPzVFxAv8ELgaqAM2i8h6Vd0XVO0OoEVVF4jIWuB+4NMishhYCywB5gCviMgid59Qbf6Dqj4bgeNLWDXNnbR09llHdoQN94V968ris9s5Gcn8+q5LeOj1Kh56o5I3Dzbw3z40j2sWz2TBjGmIrQliJplwrkmsACpV9TCAiKwD1gDBiWIN8E13+1ngB+L837AGWKeqPUC1iFS67RFGm2YcNlU3A7C8JCfGkSSmFJ+XL1+9iI9fOJtvvLCX7750gO++dICSvHQuLs5hZmYqMzNTyEpLwusRfB4PSV4hPdnH0aYOMpJ95E5Lfs9CU+EkKWOiIZxEUQjUBj2vA1YOV0dV+0WkDchzy98ZtG+hux2qzftE5BvAq8A9bqKZNE6e7o55v8DGqibyMpJZNNNmjI2lhTOn89Sdq6hv6+LV/ad4df9JNlU3c+pMN33+0GMukn0eZmelUpKbwap5uWSn2zK2JjbC+TYb6jx58L/w4eoMVz5U38hAm/cCJ4Bk4BHga8C33heUyJ3AnQDFxfHzF9Xuujb+y8Nv0x9QctOTmZOdxpXnzmDmBI6MVlU2VDWxan6eXeaIseCzAI8IVy+exdWLIaBKZ6+fnj4/AXWe9/uVPn+APn+A0919HG/t5nhrF29VNvB2ZSPLirO5bFEB+dNSYnhEJhGFkyjqgKKg53OB48PUqRMRH5AFNI+w75DlqlrvlvWIyE+Brw4VlKo+gpNIKC8vj4vhsD39fv7+lzvIzUjmMytL+MOeExw6dYbG9h7uumLBhK1XXd3YwYnT3VwyP29C3s8Mf1loOB4RpqX4mBbizHN5ifOzpbOXPx1qZMuRZrbXtLJm6RzKS3PHE64xoxLOXU+bgYUiUiYiyTid0+sH1VkP3O5u3wy8ps7SX+uBte5dUWXAQmBTqDZFZLb7U4AbgT3jOcCJ9MDLhzh4sp1v33QhX7xqIZ9dVcKNSwupb+tm29GWCYtjg7uYziXz8yfsPU305KQnc8NFc/iHa8+hrCCD57cf4/e76wnY6npmgox4RuH2OdwNvAR4gcdUda+IfAvYoqrrgUeBX7id1c04X/y49Z7B6aTuB+5SVT/AUG26b/mEiBTgXLbaAXwhcocbPVuPNvPIH6tY+4EirjhnxtnyCwqz2FDVxH/uO8kFhVmkJHmjHsvGqiay0pLYUNloK7BNIdNTk7h9dSm/3XWcP1U20tjew9oV8XPZ1UxdYfW4quqLwIuDyr7Eb8FeAAATQUlEQVQRtN0NfGqYfe8D7gunTbf8ynBiiifdfX6++stdzM5K4+sfO+89r4kIH7tgNg+/WcWbBxuiPlo3EFA2Hm5iXn6G9U9MQV6PsGZpIQXTU/jtrnqe31bH51aX2O/aRJWNzI6AP+w5QXVjB/984xKmpya97/Wi3HSWFmXzVmUjLR29UY3l4KkzNHf0Mr/A7naayi6Zn881i2eys66Nf3vFlmM10WWJIgKerKihNC+dyxfNGLbOtUtmIQKvHzgV1Vg2VDqXmuYVZET1fUzsfXhRActLcvj+q4f41XabiNBEjyWKcao8dYZNR5pZu6IYj2f40/+stCQumpvNrro22nv6oxbPhqomSvPS7Z77BCAirFk6h9Xz8vjas7vPrmZoTKRZohinJytqSfIKNy+fO2LdD5Tm0usP8Judg+8ujox+f4CKw02stttiE4bP4+FHn11OwfQUvvjUds5098U6JDMFWaIYh+4+P89tq+OaJbPCGgQ1NyeNGdNTWLe5dsS6Y7H3+GnO9PSz2m6LTShZ6Un8+y1LOdbaxf/69R7Ubps1EWaJYhx+v6eetq4+PhPmLYoiwgdKc9lZ28r++tMRj+elvSfweoRL7Ywi4SwvyeVLVy3khR3HeW7bsViHY6YYSxTj8FRFLaV56ayaF/4X89KibJK9Hp6O8FmFqvLbXfVcMj+PPJviISH97RULWDUvl2+8sIfDDe2xDsdMIZYoxmigE/uWETqxB8tI8XHNkpn8avsxuvv8EYtnV10bNc2dfOLCORFr00wuXo/wb59eRrLPw5ee3kGfPxDrkMwUYYlijJ7eXIvPI9wURif2YGs/UExbVx8v7T0RsXh+u+s4SV7hWlt+M+EEL2702runuP782eyqa+PfXjkY69DMFGGJYgx6+wM8v+0YV503Y0wzeV4yP4+i3LSIrVoWCDiXnS5bWEBW+vsH/JnEcn5hFuUlOTz0RhUVh20KFzN+lijG4LV3T9LU0cunP1A0cuUheDzCrStKqKhu5tDJM+OOZ1tNC/Vt3XziIrvsZBwfu3A2JbnpfPnpHbR12i2zZnwsUYzB05trmZmZwmULC8bcxl+UzyXZ6+H/vXN03PH8ZudxUnwePrJ45rjbMlNDis/Lv61dxqkzPXz12Z0EAnbLrBk7SxSjdKKtmzcPNnDz8rn4vGP/+PKmpXD9BbN4ftsxOsYxUtsfUH63+wRXnjsj5NoGJvEsLcrm3uvP4+V9J/mPPx6OdThmErNEMUrPbq0loPAX5WO77BTsttUlnOnp54UdYx+p/c7hJhrbe/i43e1khvBfLy3lYxfO5rsvvcuGqsZYh2MmKUsUoxAIKM9sqWPVvFxK8sY/6d7FxTmcNzuTX7xzdMyjaX/0ZhW5Gclcee7wExKaxPRkRQ1PbaqlvDiHvIwU/tvPt/LwG1WxDstMQpYoRuHtqkZqmjvH3Ik9mIhw26oS9tefZlvN6Cd023ykmT8dauQLH55HWnL0F0Qyk1NKkpfPrCymzx/gZxuqae2M7lT3ZuqxRBEmVeXBVyuZmZnCR8+fHbF21yydw/QUH4+9XT3qfR94+SD505L57KqSiMVjpqYZmanctqqEpvZe/vKnm8fVL2YSjyWKMG083MSmI838zYfnkxrB5UwzUnzcfkkpv9tVz6bq5rD3e+dwExuqmvjCh+eTnmyd2GZk8wumsfYDxew+1sadv9gS0ZkBzNRmiSJM33/lEDOmp0RljeK7rlhAYXYa//jrPWFNu6CqfO/lgxRMT7GzCTMqi+dk8p2bLuTtyib+8qebaI7yiotmarBEEYZ3DjdRUd3M31we2bOJAWnJXr7xicUcOHmGxzccGbH+mwcb2FTdzN9GKR4ztd20fC7fX7uU7TWtfOLBt9h3PPIzGZupxRJFGL7/yiEKpqdwSxTOJgZcs3gmV5xTwAMvH+REW/ew9fbXn+aLT21nXn5GVOMxU9uapYX88gur8QeUmx7ewFObavDboDwzDEsUI3jzYAMbDzt9AdH8611E+OYNS+gLKP/w7M4hp12oaerkc49tIj3Zx8/vWGFnE2ZcLpybzfr/fikXzs3i3ud384kH37KxFmZIlihCqG3u5EvrtrNgxjQ+szL6f72X5GXwvz+xmA1VTVz3/T+yodL5n7bfH2B3XRuffbSCPn+AX9yxgrk56VGPx0x9M6ansu7OVTx4yzLauvq49ccVrH1kI89traOz1+6MMg6ZCssmlpeX65YtWyLaZmdvPzc9vJG6lk7W3/1ByvJHP8BuuNlhbx0h6eysbeXLT+/gcGMHS4uyOXjyDJ29ftKTvTzxVytZVpwz5vc2Zjh9/gDdfX6eqKihprmT9GQvV5w7g1Xz8lg9L5f5BdMQCX/tFRP/RGSrqpaPVM/uqxyCqvI/nt3FuydO89O//MCYksR4XFSUze+++CG++9IBtte28Knlc1lWnMPq+XnMzEx9T11LCCZSkrwekrwe/vqyeRxp6mR7TQt/OtjA73bVA5CVlsQ5s6Zz3qzpLJw5nbL8DErzM5idmTqqxbvM5BNWohCR64DvA17gJ6r67UGvpwA/B5YDTcCnVfWI+9q9wB2AH/iiqr4Uqk0RKQPWAbnANuA2VZ2we/hOnenmn36zj9/tqudr153L5efEZmqMgTuhjJloIkJZfgZl+RmoKs0dvVQ3dlDX2sWJtm521LbS2//n27iTvR5mZqUwOyuNWZmp5GYkk5eRTHZGMtNSvGQk+8hI8ZGa5CHF5yU1yUuKz0NqkpfUJA/pyT68lmji2oiJQkS8wA+Bq4E6YLOIrFfVfUHV7gBaVHWBiKwF7gc+LSKLgbXAEmAO8IqILHL3Ga7N+4EHVHWdiPzIbfvhSBxsKP3+AE9truU7f3iXnv4AX71mEV/48Lxov60xcU1EyJuWQt60FAauTwRUOd3VR1NHL/MKMqhp7uREWzf1rd3srGuluaOXM92j699ITfIwLcXH9NQkMtOSyEz1kZOeTG5GsvszidyMFCcJTXPKstOTSBrHDM4mfOGcUawAKlX1MICIrAPWAMGJYg3wTXf7WeAH4lzMXAOsU9UeoFpEKt32GKpNEdkPXAnc6tZ53G03Komi8lS7c1dTVSMV1c2c6e7n0gV5/MuNF0z45SZjJguPCNnpyWSnJwNQkptBSe57/3/pDwTo6vXT0x9wH376/Uq/P0CfX+nzB+gLOM97z9Zx+kg6e/ppau9hb+9pOnv76e4bfhDq9BSfk1jSkpie4iMlyUNakpdknwevR/CKICIEVAmo4g8E/3TaqGvpco+Ls/v4vMKSOVmkJnlJS/KSluy0m5LknBGl+jwk+5xLdT6PU19k4P2cdgVnW8TZ9noEr8f5/HweD16vkORxygee+9znXpG4upwXTqIoBGqDntcBK4ero6r9ItIG5Lnl7wzat9DdHqrNPKBVVfuHqB9xP327micqaijNS+fjF87mynNn8pHzZsSsw26snd/GxBufx8P0VA/TI9CWP6B09PbT0dNPR4+fzt5+OnqdhNLV56e7z09XX4DG9h76/AEyUnz09gfwuwlBFTwe6Ozxu1/cgkf+/EUOoMp7kkl/QNl9rM1JbjEaXyLiJJWBWN3/ziaegTr/cdtyPjSORdTCEU6iGOpbc/AnN1yd4cqHOl8MVf/9QYncCdzpPm0XkQND1QvHUeBN4NsjVRy9fOB9N6Z/ZpSNjLb+GA0ZaxybTPFOplhhcsU7mWKFKMR72T+Pa/ew5gAKJ1HUAcHzas8FBq+0M1CnTkR8QBbQPMK+Q5U3Atki4nPPKoZ6LwBU9RHgkTDijxkR2RLOrWfxYDLFCpMr3skUK0yueCdTrDD54h0QTk/QZmChiJSJSDJO5/T6QXXWA7e72zcDr6kzQGM9sFZEUty7mRYCm4Zr093ndbcN3DZfGPvhGWOMGa8RzyjcPoe7gZdwbmV9TFX3isi3gC2quh54FPiF21ndjPPFj1vvGZyO737gLlX1AwzVpvuWXwPWici/ANvdto0xxsTIlBiZHa9E5E73Elncm0yxwuSKdzLFCpMr3skUK0y+eAdYojDGGBOSjVYxxhgTkiWKKBCR60TkgIhUisg9sY4HQESKROR1EdkvIntF5O/c8m+KyDER2eE+rg/a5173GA6IyLUTHO8REdntxrTFLcsVkZdF5JD7M8ctFxH5dzfWXSJy8QTHek7Q57dDRE6LyJfi5bMVkcdE5JSI7AkqG/VnKSK3u/UPicjtQ71XFOP9roi868b0KxHJdstLRaQr6DP+UdA+y91/Q5XuMUV8gNQwsY769x6P3xnvoar2iOADp3O+CpgHJAM7gcVxENds4GJ3ezpwEFiMM/L9q0PUX+zGngKUucfkncB4jwD5g8q+A9zjbt8D3O9uXw/8HmccziqgIsa//xM496fHxWcLXAZcDOwZ62eJM/faYfdnjrudM4HxXgP43O37g+ItDa43qJ1NwGr3WH4PfHSCYh3V7z1evzOCH3ZGEXlnpzxRZzLDgSlPYkpV61V1m7t9BthP6FHvZ6dfUdVqIHj6lVhZgzOtC+7PG4PKf66Od3DG4syORYDAVUCVqh4NUWdCP1tV/SPO3YiDYxjNZ3kt8LKqNqtqC/AycN1Exauq/6l/nrHhHZwxVsNyY85U1Y3qfEv/nD8fY1RjDWG433tcfmcEs0QReUNNeRK1aUjGQkRKgWVAhVt0t3tK/9jAJQhifxwK/KeIbBVnFD7ATFWtByfxAQNT+8Y61mBrgaeCnsfjZwuj/yzjIeYB/xXnDGFAmYhsF5E3ReRDblkhTowDJjre0fze4+mzHZIlisgLexqSWBCRacBzwJdU9TTOhIvzgaVAPfCvA1WH2H0ij+NSVb0Y+Chwl4hcFqJurGN1gnAGj94A/NItitfPNpTRTsczoUTk6zhjsp5wi+qBYlVdBnwFeFJEMoltvKP9vcfFZxuKJYrIC2fKk5gQkSScJPGEqj4PoKonVdWvqgHgx/z5EkhMj0NVj7s/TwG/cuM6OXBJyf15Kh5iDfJRYJuqnoT4/Wxdo/0sYx6z24H+ceAz7uUk3Ms4Te72Vpxr/YvceIMvT01YvGP4vcf8sx2JJYrIC2fKkwnn3vHxKLBfVb8XVB58Lf+TwMDdG8NNvzIRsWaIyPSBbZyOzD28d6qY4Old1gOfc+/YWQW0DVxWmWC3EHTZKR4/2yCj/SxfAq4RkRz3Uso1btmEEGehs68BN6hqZ1B5gThr5iAi83A+y8NuzGdEZJX7b/9zTNB0QGP4vcfld8Z7xLo3fSo+cO4cOYjz183XYx2PG9MHcU5ndwE73Mf1wC+A3W75emB20D5fd4/hAFG4YyRErPNw7vzYCewd+AxxpqF/FTjk/sx1ywVnIawq91jKY/D5puOs7pgVVBYXny1O8qoH+nD+er1jLJ8lTt9Apfv4/ATHW4lzHX/g3+6P3Lo3uf9GduKsiPmJoHbKcb6kq4Af4A4wnoBYR/17j8fvjOCHjcw2xhgTkl16MsYYE5IlCmOMMSFZojDGGBOSJQpjjDEhWaIwxhgTkiUKk1BEZKaIPCkih93pQTaKyCdjHNMLIrIxljEYE4olCpMw3IFXvwb+qKrzVHU5zuCmkBPMBe3vjUJM2Tizj2a7g7CGqjPiksXGRJMlCpNIrgR6VfXsmgWqelRVH3TXNfiTiGxzH5cAiMjl4qzj8STOICpE5Nfu2cjeoAkLEZE7ROSgiLwhIj8WkR+45QUi8pyIbHYflwbFdBPwG5wZQ9cGtfUzEfmeiLwO3O+OVn/M3X+7iKxx6w0ZtzGRZAPuTMIQkS8CZar65SFeSwcCqtotIguBp1S1XEQuB34HnK/O1NCISK6qNotIGs70Cx/GWWNgA87ZwRngNWCnqt7tJpmHVPUtESkGXlLV89y2XgH+CTgJPKuqF7rlPwPygTWq6heR/wPsU9X/556FbMKZAViHijvyn55JZHZKaxKWiPwQZ2qTXuAjwA9EZCngx5lYbsCmgSTh+mJQv0YRzpw9s4A3VbXZbfuXQW18BFgsf15gLdOdyyodWAC8paoqIv0icr6qDswN9EtV9bvb1wA3iMhX3eepQDHO5HHDxW1MRFiiMIlkL86lHgBU9S4RyQe2AF/G+av+IpxLst1B+3UMbLhnGB8BVqtqp4i8gfOlHWqZTY9bvyu4UEQ+j7NaXLWbRDJxLj/9r8Hv67Z/k6oeGNTGN0PEbUxEWB+FSSSvAaki8jdBZenuzyygXp2poW/DWZ5yKFlAi5skzsVZLhScS0EfdmdX9RGUkID/BO4eeOL+9Q/ObLPXqWqpqpYCA53rQ3kJ+O9uhzwismyUcRszZpYoTMJQp0PuRpwv9GoR2YSzDOjXgIeA20XkHZzLNx3DNPMHwCciu4B/xlmWE1U9BvwfnFUDXwH2AW3uPl8EysVZ8Wwf8AVxVhksHtjfbaMaOC0iK4d4338GkoBdIrLHfc4o4jZmzKwz25gIEZFpqtrunlH8CnhMVX8V67iMGS87ozAmcr4pIjtw1kCoxhmzYcykZ2cUxhhjQrIzCmOMMSFZojDGGBOSJQpjjDEhWaIwxhgTkiUKY4wxIVmiMMYYE9L/B1eLIhMAxREFAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['GarageArea'].fillna(0))\n",
    "df['GarageArea'].fillna(df['GarageArea'].mean()).skew()\n",
    "# df[df['GarageArea'].isnull()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "((array([-3.4943654 , -3.25015084, -3.11507391, ...,  3.11507391,\n",
       "          3.25015084,  3.4943654 ]),\n",
       "  array([   0.,    0.,    0., ..., 3200., 3206., 5095.])),\n",
       " (421.46822237763234, 1048.967775111416, 0.9804724671118593))"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "stats.probplot(df['TotalBsmtSF'], plot=ax)\n",
    "# sns.distplot(df['TotalBsmtSF'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1stFlrSF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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uk9YQflBnusJ9VGbG+RUFHGjqpLN3wOtyZIpQuMukDT2FWZavbpkzuaCygKCDnXW6epf4ULjLpDW09zItJ52MwNSdU2YsM/IzKc3NUNeMxI3CXSbteHsP03Uz9azMjAsqCzjcfIr27n6vy5EpQOEuk9I7MMiJzl6mF6i/fSznVxbggF317V6XIlOAwl0m5UDjKYJON1MjUZqbQX5mgEPNp7wuRaYAhbtMyt7wotAaBjk2M6O6JIcjJ06hSVMl1hTuMimvHe/Ab0ZJrvrcI1FdnEN7zwAtXep3l9hSuMuk7G3ooDQvA79vtNUYZaTq8Lqqh0+oa0ZiS+Euk7LneIfGt49DWX4GWWl+DqvfXWJM4S4T1tHTT21rt/rbx8FnxuzibA6f6PK6FElxCneZsKGbqRopMz7VxTk0d/ZqKgKJKYW7TNie46EFOnTlPj7VxdkA6pqRmFK4y4TtOd5OTrqfguw0r0tJKuVFWaT5jSO6qSoxpHCXCdvT0MGCGXn4TCNlxiPg81FZpH53iS2Fu0yIc449xztYqAWxJ6S6OIe61m56+7U6k8SGwl0m5Hh7Dy1d/Zw3M9/rUpJSdUk2Djh6UlfvEhsKd5mQXXWhya8WlyvcJ2LWtGwMOKJwlxiJKNzN7CYz22Nm+83s82do8xdmtsvMdprZI9EtUxLNzrp2zOBcXblPSEbAT2leBnWt3V6XIikqMFYDM/MD9wNvAWqAjWa22jm3a1ib+cAXgMudcy1mVhargiUx7Kxro7o4h9yMMf8IyRlUFGZxoKnT6zIkRUVy5X4xsN85d9A51wc8Btw6os2Hgfudcy0AzrnG6JYpiWZnXTuL1CUzKeWFWbT3DNDY0eN1KZKCIgn3CuDYsNc14feGWwAsMLMXzWy9md0UrQIl8bR191PT0s0idclMSnlhFhD6h1Ik2iIJ99EGMY+cjDoAzAeuBu4AHjKzwjfsyOxeM9tkZpuamprGW6skCN1MjY6Z4dWrdtZqXVWJvkjCvQaoGva6Eqgbpc0vnXP9zrlDwB5CYf86zrkHnHMrnHMrSktLJ1qzeGxnXSiMFpcXeFxJcstM81Ock86OWl25S/RFEu4bgflmNsfM0oHbgdUj2jwJXANgZiWEumkORrNQSRy76tspzcugVItiT1p5YRY76nTlLtE3Zrg75waATwBrgd3A4865nWb2FTNbFW62FjhhZruA54C/cc6diFXR4q1dde3qkomSisIsalq6ae3q87oUSTERjWNzzq0B1ox470vDfnbAX4d/SYp6ZMNR+geD7G3oYEZ+Jo9sOOp1SUlv+E3Vy+eVeFyNpBI9oSrj0tDeQ9DBzHAoyeSUh2+q7tBNVYkyhbuMS31baEz2UCjJ5GRnBKgozGKHhkNKlCncZVzqWrvJCPgoykn3upSUsaQiX8MhJeoU7jIu9W09zCzI1BzuUbSkvICDzafo6On3uhRJIQp3iVjQOY639TCzQP3t0bSkIvS8wO76Do8rkVSicJeINXX00jcYpEI3U6NqcUVoWOl2dc1IFCncJWI1LaHpaSuLFO7RVJaXSVlehvrdJaoU7hKxmpYuMgI+SvRkatQtKs9nV71GzEj0KNwlYjUt3VQUZelmagwsLs9nf2MnPVpTVaJE4S4R6ekfpL6tm6qibK9LSUmLywsYCDr2NWjxDokOhbtEZFd9O0Gn/vZYGZobf6cmEZMoUbhLRLYdawWgUlfuMTFrWja5GQH1u0vUKNwlItuOtZKfGaAgK83rUlKSz2ecNzNPqzJJ1CjcJSKv1rRRoav2mFpcXsDu+naCwZELnYmMn8JdxtTW1c/B5lNUqb89phbNzKerb5DDJ055XYqkAIW7jOnVWvW3x8Oi8AIo6neXaFC4y5iGbqZq2oHYmj89l4DP1O8uUaFwlzFtPdbG3NIcstL9XpeS0jICfuZP101ViQ6Fu5yVc46tx1pZVlnodSlTwqKZ+exSuEsUKNzlrOraemju7OWCygKvS5kSFpfn09zZS2N7j9elSJJTuMtZbTx0EoAV1dM8rmRqGLqpulM3VWWSFO5yVq8cPkleRoDzwo/HS2ydHjGjrhmZJIW7nNUrh06yvLoIv08zQcZDfmYas6Zls71Gc8zI5Cjc5YxOnupjf2Mnb1KXTFwtrSpkW02r12VIkoso3M3sJjPbY2b7zezzZ2l3m5k5M1sRvRLFKxsPh/rbL56jcI+nZVWF1Lf10KCbqjIJY4a7mfmB+4GbgUXAHWa2aJR2ecCngA3RLlK8sfHQSdIDPo2UibNlVaH/31uP6epdJi4QQZuLgf3OuYMAZvYYcCuwa0S7rwL/DHw2qhVK3D2y4SgAz+w4TnlBJj/bXOtxRalt6P/3kP7BID4LvX/j4hkeVSXJLpJumQrg2LDXNeH3TjOzC4Eq59yvzrYjM7vXzDaZ2aampqZxFyvx0zsQWnmpuiTH61KmnDS/j5kFWRw72eV1KZLEIgn30YZJnJ6T1Mx8wH3AZ8bakXPuAefcCufcitLS0sirlLg7erKLoIPqYoW7FyqLsqht7WZQ0//KBEUS7jVA1bDXlUDdsNd5wBLgeTM7DFwKrNZN1eR2uLkLI7RCkMRfVVE2vQNBDjRpTVWZmEjCfSMw38zmmFk6cDuwemijc67NOVfinKt2zlUD64FVzrlNMalY4uLwiVPMLMwkM02ThXmhclpoBs6tR3VTVSZmzHB3zg0AnwDWAruBx51zO83sK2a2KtYFSvwNDAY5drKLOeqS8UxJbgaZaT62ary7TFAko2Vwzq0B1ox470tnaHv15MsSLx1r6WYg6HQz1UM+MyqLsnXlLhOmJ1TlDfY2dOAzOKc01+tSprTKoiz2NHTQ3TfodSmShBTu8gZ7GzqYNS1H/e0eqyrKZjDo2FGneWZk/BTu8jqN7T3Ut/WwYLqu2r1WFR6ppK4ZmQiFu7zO83tDD5ctmJ7ncSWSmxGgsiiLLcdavC5FkpDCXV7n93uayMsMMLMg0+tShNCkbS8fOEFQDzPJOCnc5bSBwSDr9jWxoCwPM83fngiunF9CS1c/u7Qyk4yTwl1O23qslfaeARbMUJdMorh8XgkA6/Y1e1yJJBuFu5z2/J4m/D5jnoZAJoyyvEzOnZHHC/s10Z6Mj8JdTnt+byMXzSokK11DIBPJFfNK2Hi4hZ5+jXeXyCncBYCmjl521LZz9cIyr0uREa6YX0LfQJBXDp30uhRJIgp3AWDtzuMAXKNwTziXzCkm3e/jhf3qd5fIKdwFgNVb65hXlst5M3UzNdFkpftZPrtIN1VlXBTuQk1LF68cPsnblpVrCGSCumJ+Cbvr22nq6PW6FEkSCndh9bbQ2iu3LqsYo6V45cr5oSGRLx3Q1btERuEurN5ax0WzCk/PZSKJZ3F5AYXZaeqakYgp3Ke4146389rxDt52oa7aE5nfZ1w5v5TfvdZI/2DQ63IkCSjcp7hfbq3D7zNuOX+m16XIGFYtLefkqT6NmpGIKNynsGDQsXprHVfOL6EkN8PrcmQMVy0opSArjdVb68ZuLFOewn0K23j4JLWt3dy6rNzrUiQC6QEft5w/g7U7j9PVN+B1OZLgFO5T2A9fOkx+ZoAbF8/wuhSJ0KqlFXT1DfLs7kavS5EEp3Cfoo6e6GLtzuPceelsstMjWiddEsDFc6YxIz+T1VtrvS5FEpzCfYr6wUuH8Jnx/pXVXpci4+D3GX++dCbP72mi5VSf1+VIAlO4T0Ft3f08vvEYq5aWM0MrLiWdW5dVMBB0PLPjuNelSAKLKNzN7CYz22Nm+83s86Ns/2sz22Vmr5rZb81sdvRLlWh57JWjnOob5INXzPG6FJmAxeX5zC3N4ckt6pqRMxsz3M3MD9wP3AwsAu4ws0Ujmm0BVjjnLgCeAP452oVKdPQPBvnhS4dZObeYJRUFXpcjE2BmvGt5Fa8cPsluLb8nZxDJnbSLgf3OuYMAZvYYcCuwa6iBc+65Ye3XA3dFs0iJntVb66hv6+Frb1/idSkSgUc2HB31/TS/keY3vvjkDt5xUeXp999zyax4lSYJLpJwrwCODXtdA1xylvYfAp6ZTFESPcPDoW8gyH3P7qWiMIurF2je9mSWnR5gWVURW462cOPiGeRkaMSTvF4kfe6jzQHrRm1odhewAvj6Gbbfa2abzGxTU5PWhIy3F/Y309bdzy3nz8Tn09S+ye6yc4oZCDo2HtYKTfJGkYR7DVA17HUl8Ibnn83seuBvgVXOuVEnnXbOPeCcW+GcW1FaWjqRemWC2nv6+cPeJhaX5zOnJMfrciQKpudnMq80l/UHTzAYHPV6S6awSMJ9IzDfzOaYWTpwO7B6eAMzuxD4LqFg16NzCejZXQ0MBh036WnUlHLZOcW09wywo67N61IkwYwZ7s65AeATwFpgN/C4c26nmX3FzFaFm30dyAV+amZbzWz1GXYnHqhr7WbzkRZWnlNMsSYISykLZuRRnJPOS/ubcU5X7/InEd2Fcc6tAdaMeO9Lw36+Psp1SZT0Dgzyk03HyE73a/HrFOQz4/J5JazeVseBplNelyMJRLfYk8yZhsaNNgTOOccvt9bR3NHLBy6fQ1a6f8z9SPJZMbuI5/c08tvdDXzxredpHVwBNP1ASnvklaNsPdbKdeeVMa8s1+tyJEYCfh9XLyzjyMkuXtx/wutyJEEo3FPUH4+28PerdzG/LJer1R2T8lbMLqIgK41/e3av+t4FULinpKe21fGeB9dTlp/BX6yowqev6Skv4Pdx1YJSNh1p0dW7AAr3lBIMOr6+9jU++egWlpQX8IuPXa4nF6eQFbOLmFmQyX26ehcU7ikh6By/3lHP27/1Ivc/d4A7Lq7ikQ9fSmmehj1OJQG/j09eO5/NR1p4enu91+WIx3RZl8T6BoJsPdbKC/ubae7sZda0bP7lXUt5x0UVGjExRb37TVU8vP4IX3t6N9csLNM3tylMZz4JtZzq46UDzWw+2kJPf5Dygkz+844LuXnJDAJ+fRmbyvw+46tvW8w7v/0y9z+3n8/ddK7XJYlHFO5JpKd/kN++1sDv9zQRdI4lFQWsnFvMrGnZ/PnScq/LkwSxfPY03nlRJQ+uO8htyyuZW6phsFORLvOSxEsHmrn539fx292NnDczn7+58Vxuf9MsZhfnqAtG3uB/37yQzICfLz+1SzdXpyiFe4JzzvHQuoPc9dAGnHN84PJq7rh4FgVZaV6XJgmsLC+Tv75hAX/Y28QPXjzsdTniAYV7AusbCPL5n23nH57ezY2LZ7Dmf13J/LI8r8uSJPH+ldXcsGg6X1uzm/UHNfZ9qlGfe4Lq7B3gnv/ayPqDJ/nktfP49PULtMCGjGnknEGXzi1my9FWPv7ff+SpT15BeWGWR5VJvOnKPQG1dfVz50Mb2HS4hfvevZTP3LBQwS4Tkpnm565LZ9M7EOQjD2+mvaff65IkThTuCeZEZy93PLie3XXtfOvOi3j7hZVj/yaRsyjNy+Df3r2MXXXtvP3+FznUrKmBpwJ1y3ho5Ffo9p5+vvfCIVpO9fG9u9/EVQu0FKFEx/WLpvPwPZfw0Yc3c+s3X+Cb77mINy8oPevUz6NNIy3JQ+GeIFq7+vjeC4fo6Bng7suqqW3pHtec65qfXcZy6dxiVn/iCj78o03c/YNXeNfyKqpLcjTyKkUp3BPAyVN9PPTCQbr7Bvng5dXMKtYC1hIbVdOy+dlHL+Nf/2cvP375CEHnuOycYq6YX0qupipIKepz91h9WzcP/OEAvf1B7rliroJdYi4nI8AX37qI337mKs6vKGDdvma+vvY1Vm+r5eSpPq/LkyjRP9Ue2nO8g0c3HiUz4OPDV85lRkGm1yXJFFI1LZt3rajiqoWlrNvXzMZDLbxy6CTLqoq49lwt8JLsFO4eeXj9EX68/jDT8zN538pq9XuKZ8ryMnnnRZVcf950XtjXxIZDJ9l6rIXa1i4+ee18jY1PUubVvBMrVqxwmzZt8uSzvXTyVB9ffHIHT2+vZ+H0PG6/uIqMgH/s3ygSJ+3d/Ty/t4k/HmnBDO6+vJqPXTWPgmxdgCQCM9vsnFsxZjuFe/ys3Xmcv/3Fdtq6+/mr6xeQn5mGXw8nSYJ684IS/vV/9vKLLbXkZQT4y6vO4X0rZ5PRZYsCAAAJXElEQVSXqZD3ksI9QTjn+PundvHcnkaOnOhiZkEmty2vZGaBvupKYhsa5767vp2vr93D715rJD8zwAevmMP7V1ZTlJPucYVTU1TD3cxuAv4d8AMPOef+ccT2DOBHwHLgBPBu59zhs+0z1cO9pqWL3+xs4OdbathR205BVhpXzi/h4jnTCPg0SEmST21LN7/b08ju+nbS/T7esmg6t62o5Mp5JVokJo4iDfcxb6iamR+4H3gLUANsNLPVzrldw5p9CGhxzs0zs9uBfwLePbHSk8+p3gGOnOhiZ10bO+va2Xj4JDvr2gE4d0Ye77iwgmWzChXqktQqirJ476WzWT67iMc2HuXJLbU8vb2evMwAl8wpZuU5xVw4q5BzSnLVP58AxrxyN7OVwJedczeGX38BwDn3/4a1WRtu87KZBYDjQKk7y85jceXunGMw6BgIOvoHg/QOhH/1D9LdP0hPf5Ce/kF6+gfD2wbpH3D0DQYZGAwyEPzT7//Tf4P0Dzr6wvvq6R+ko6ef9p4BWrv6qG/roaNn4HQN2el+lpQXcN15ZdyweAZzSnL09KiklKHumr6BIL97rZHf723k5QMnOHyi63Sb4px0KouyKMpJZ1pOOvmZaWSn+8lK85OV7icj4CMj4Cc94CPN7yPNb6T5ffh8ht8Mn4EjtPi7czDoHMGgIzgsUQwI+I10v4+0gI90v4/MtNC+h/Yb+q/hMzt9f8s5cDiCQU7/3e8fdPQOhHOhP0jfYOjngUF3ugaHw+/zkeYzAn5f6BjSQp+bkeYnPfx56X4fAb8R8FlMFtKJ2pU7UAEcG/a6BrjkTG2ccwNm1gYUA82RlRu5X++o569+spXQZ4X+ADgXOumDwejfP/BZaF3KgM9HwGcE/MbMgizyMgNUF+ewcm4xMwqyqCzK4mDTKYpz0/GFT+jLB07w8gHNoy2pZeTFyvkVhZxfUXj6Yqe5s5fmzl7auvtpbuikq2+A7v5B+gaCxOCvaEIbyg8zw4ChrP/wlXP5zA0LY/rZkYT7aP/0jDxFkbTBzO4F7g2/7DSzPcM2lxCDfwxiYeuZNyXNMZxFsh9DstcPOoZEEbNj+Gz41wTNjqRRJOFeA1QNe10J1J2hTU24W6YAODlyR865B4AHRvsQM9sUyVeNRKZj8F6y1w86hkSR7McQyR2+jcB8M5tjZunA7cDqEW1WA+8P/3wb8Luz9beLiEhsjXnlHu5D/wSwltBQyO8753aa2VeATc651cD3gB+b2X5CV+y3x7JoERE5u4jmlnHOrQHWjHjvS8N+7gHeNclaRu2uSTI6Bu8le/2gY0gUSX0Mnj2hKiIisaOnakREUlDcw93MDpvZdjPbamZveIrJzK42s7bw9q1m9qXR9uMlMys0syfM7DUz2x1+0Gv4djOz/zCz/Wb2qpld5FWto4mg/oQ+B2a2cFhtW82s3cz+akSbRD8HkRxDQp8HADP7tJntNLMdZvaomWWO2J5hZj8Jn4cNZlbtTaVnFsEx3G1mTcPOwz1e1Touzrm4/gIOAyVn2X418Kt41zXOY/gv4J7wz+lA4YjttwDPEBr/fymwweuax1l/wp+DYbX6CT0RPTuZzkGEx5DQ54HQw4uHgKzw68eBu0e0+RjwnfDPtwM/8bruCRzD3cA3va51vL/ULTNOZpYPvJnQCCGcc33OudYRzW4FfuRC1gOFZjYzzqWOKsL6k8l1wAHn3JER7yfsORjFmY4hGQSArPDzLdm88RmYWwldTAA8AVxnsXgmf3LGOoak5EW4O+A3ZrY5/MTqaFaa2TYze8bMFsezuAjMBZqAH5jZFjN7yMxGLnw62pQNFfEqcAyR1A+JfQ6Gux14dJT3E/kcjHSmY4AEPg/OuVrgG8BRoB5oc879ZkSz101NAgxNTZIQIjwGgHeGu/eeMLOqUbYnHC/C/XLn3EXAzcDHzezNI7b/kdDX06XAfwJPxrvAMQSAi4BvO+cuBE4Bnx/RJqLpGDwSSf2Jfg4ACD9Utwr46WibR3kvUc7BaWMcQ0KfBzMrInRlPgcoB3LM7K6RzUb5rQlzHiI8hqeAaufcBcCz/OmbSEKLe7g75+rC/20EfgFcPGJ7u3OuM/zzGiDNzEriXedZ1AA1zrkN4ddPEArLkW3GmrLBK2PWnwTnYMjNwB+dcw2jbEvkczDcGY8hCc7D9cAh51yTc64f+Dlw2Yg2p8+DnWVqEg+NeQzOuRPOud7wywcJrVuR8OIa7maWY2Z5Qz8DNwA7RrSZMdQnZ2YXh2tMmKkVnXPHgWNmNjSl23XArhHNVgPvC4/YuJTQV736eNZ5JpHUn+jnYJg7OHN3RsKegxHOeAxJcB6OApeaWXa4zuuA3SPaJPrUJGMew4h7NatGbk9UET2hGkXTgV+E/7wGgEecc782s48AOOe+Q+gPwEfNbADoBm5PsD8MAJ8E/jv8lfog8IERx7CG0GiN/UAX8AGvCj2DsepP+HNgZtmEFpD5y2HvJdM5iOQYEvo8OOc2mNkThLqPBoAtwAOWRFOTRHgMnzKzVeHtJwmNnkl4ekJVRCQFaSikiEgKUriLiKQghbuISApSuIuIpCCFu4hIClK4S8ows++bWaOZ7Rij3dVmdtmw1182s9phs/79Y/j9581s1DU0zeyt4ekbtpnZLjP7y7PtSyTe4j3OXSSWfgh8E/jRGO2uBjqBl4a9d59z7huRfIiZZRBapedi51xN+HX1RPYlEiu6cpeU4Zz7AyMebTezT4WvrF81s8csNJ/4R4BPh6+sr4xk32bWaWZfMbMNwCWELoxOhD+31zm3J5rHIjJZCndJdZ8HLgxP+vQR59xh4DuErq6XOefWhdt9elhXyo2j7CcH2OGcuyT8j8hq4IiFFne408yG/10aa18iMadwl1T3KqGpFu4i9Pj4mQyF/TLn3NpRtg8CPxt64Zy7h9A8JK8AnwW+P459icScwl1S3Z8B9xOayW9zeGbCiehxzg0Of8M5t905dx+h+WHeObkyRaJL4S4pK9xVUuWcew74HFAI5AIdQN4k9ptrZlcPe2sZkIyrKEkK02gZSRlm9iihkTAlZlYDfBV4r5kVEFo04j7nXKuZPQU8YWa3Epohc9wfBXzOzL5LaLbGUyTJTIEydWhWSBGRFKRuGRGRFKRwFxFJQQp3EZEUpHAXEUlBCncRkRSkcBcRSUEKdxGRFKRwFxFJQf8f3VHQeiOOw4AAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.distplot(df['1stFlrSF'].apply(np.log1p))\n",
    "df['1stFlrSF'].apply(np.log1p).skew()\n",
    "df['1stFlrSF'] = df['1stFlrSF'].apply(np.log1p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23617c2b748>"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.groupby('TotRmsAbvGrd')['SalePrice'].mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23616683fd0>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train.groupby(['YearBuilt'])['SalePrice'].mean().plot()\n",
    "# train.groupby(['YearBuilt'])['SalePrice'].mean().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x23617e3a390>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df['YearRemodAdd-YearBuilt'] = df['YearRemodAdd'].apply(np.int) - df['YearBuilt'].apply(np.int)\n",
    "df.groupby('YearRemodAdd-YearBuilt')['SalePrice'].count().plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['LotArea'] = df['LotArea'].apply(np.log1p)\n",
    "# ss.distplot(df['LotArea'])\n",
    "\n",
    "# fig = plt.figure()\n",
    "# ax = fig.add_subplot(111)\n",
    "# stats.probplot(df['LotArea'], plot=ax)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['Overall'] = df['OverallCond'] * df['OverallQual']\n",
    "df['NumOfBath'] = df['BsmtFullBath'] + df['BsmtHalfBath']*0.5 + df['FullBath'] + df['HalfBath']*0.5\n",
    "df['PorchSF'] = df['OpenPorchSF'] + df['EnclosedPorch'] + df['3SsnPorch'] + df['ScreenPorch']\n",
    "df['TotalSF'] = df['1stFlrSF'] + df['2ndFlrSF'] + df['TotalBsmtSF']\n",
    "\n",
    "df = df.drop(['Utilities','Street','PoolQC'], axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Id', 'MSSubClass', 'MSZoning', 'LotFrontage', 'LotArea', 'Alley',\n",
       "       'LotShape', 'LandContour', 'LotConfig', 'LandSlope', 'Neighborhood',\n",
       "       'Condition1', 'Condition2', 'BldgType', 'HouseStyle', 'OverallQual',\n",
       "       'OverallCond', 'YearBuilt', 'YearRemodAdd', 'RoofStyle', 'RoofMatl',\n",
       "       'Exterior1st', 'Exterior2nd', 'MasVnrType', 'MasVnrArea', 'ExterQual',\n",
       "       'ExterCond', 'Foundation', 'BsmtQual', 'BsmtCond', 'BsmtExposure',\n",
       "       'BsmtFinType1', 'BsmtFinSF1', 'BsmtFinType2', 'BsmtFinSF2', 'BsmtUnfSF',\n",
       "       'TotalBsmtSF', 'Heating', 'HeatingQC', 'CentralAir', 'Electrical',\n",
       "       '1stFlrSF', '2ndFlrSF', 'LowQualFinSF', 'GrLivArea', 'BsmtFullBath',\n",
       "       'BsmtHalfBath', 'FullBath', 'HalfBath', 'BedroomAbvGr', 'KitchenAbvGr',\n",
       "       'KitchenQual', 'TotRmsAbvGrd', 'Functional', 'Fireplaces',\n",
       "       'FireplaceQu', 'GarageType', 'GarageYrBlt', 'GarageFinish',\n",
       "       'GarageCars', 'GarageArea', 'GarageQual', 'GarageCond', 'PavedDrive',\n",
       "       'WoodDeckSF', 'OpenPorchSF', 'EnclosedPorch', '3SsnPorch',\n",
       "       'ScreenPorch', 'PoolArea', 'Fence', 'MiscFeature', 'MiscVal', 'MoSold',\n",
       "       'YrSold', 'SaleType', 'SaleCondition', 'SalePrice',\n",
       "       'YearRemodAdd-YearBuilt', 'Overall', 'NumOfBath', 'PorchSF', 'TotalSF'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['HasPool'] = df['PoolArea'].apply(lambda x: 1 if x>0 else 0)\n",
    "df['HasSecFlr'] = df['2ndFlrSF'].apply(lambda x: 1 if x>0 else 0)\n",
    "df['HasGarage'] = df['GarageArea'].apply(lambda x: 1 if x>0 else 0)\n",
    "df['HasBamt'] = df['TotalBsmtSF'].apply(lambda x: 1 if x>0 else 0)\n",
    "# df['HasFirePlace'] = df['Fireplaces'].apply(lambda x: 1 if x>0 else 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SalePrice                 1.000000\n",
       "OverallQual               0.795774\n",
       "TotalSF                   0.764712\n",
       "GrLivArea                 0.702933\n",
       "TotalBsmtSF               0.651153\n",
       "GarageCars                0.641047\n",
       "NumOfBath                 0.635896\n",
       "GarageArea                0.629217\n",
       "1stFlrSF                  0.598540\n",
       "Overall                   0.566759\n",
       "FullBath                  0.562165\n",
       "TotRmsAbvGrd              0.537769\n",
       "MasVnrArea                0.480421\n",
       "Fireplaces                0.469862\n",
       "BsmtFinSF1                0.409384\n",
       "LotArea                   0.392170\n",
       "LotFrontage               0.352716\n",
       "WoodDeckSF                0.324758\n",
       "OpenPorchSF               0.321142\n",
       "2ndFlrSF                  0.320532\n",
       "HalfBath                  0.284590\n",
       "HasGarage                 0.236883\n",
       "BsmtFullBath              0.228459\n",
       "BsmtUnfSF                 0.214460\n",
       "PorchSF                   0.196875\n",
       "BedroomAbvGr              0.168245\n",
       "HasBamt                   0.152860\n",
       "HasSecFlr                 0.137953\n",
       "ScreenPorch               0.111415\n",
       "HasPool                   0.103995\n",
       "PoolArea                  0.099490\n",
       "MoSold                    0.046124\n",
       "3SsnPorch                 0.044568\n",
       "BsmtFinSF2               -0.011422\n",
       "BsmtHalfBath             -0.016881\n",
       "MiscVal                  -0.021203\n",
       "Id                       -0.021673\n",
       "LowQualFinSF             -0.025625\n",
       "OverallCond              -0.077948\n",
       "EnclosedPorch            -0.128646\n",
       "KitchenAbvGr             -0.135946\n",
       "YearRemodAdd-YearBuilt   -0.217635\n",
       "Name: SalePrice, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.corr().sort_values(by=['SalePrice'], ascending=False).SalePrice"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Modeling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Voyager\\Anaconda3\\lib\\site-packages\\sklearn\\cross_validation.py:41: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. Also note that the interface of the new CV iterators are different from that of this module. This module will be removed in 0.20.\n",
      "  \"This module will be removed in 0.20.\", DeprecationWarning)\n",
      "C:\\Users\\Voyager\\Anaconda3\\lib\\site-packages\\sklearn\\grid_search.py:42: DeprecationWarning: This module was deprecated in version 0.18 in favor of the model_selection module into which all the refactored classes and functions are moved. This module will be removed in 0.20.\n",
      "  DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.grid_search import GridSearchCV \n",
    "from sklearn.model_selection import train_test_split, cross_val_score\n",
    "from sklearn.linear_model import LassoCV, Lasso\n",
    "from sklearn.svm import SVR\n",
    "\n",
    "import lightgbm as lgb\n",
    "from xgboost import XGBRegressor"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_copy = df.copy()\n",
    "df_y = np.log1p(df_copy['SalePrice'])\n",
    "df_copy.drop(['Id', 'SalePrice'], axis=1, inplace=True)\n",
    "df_x = pd.get_dummies(df_copy)\n",
    "x = df_x[:len(train)-2]\n",
    "y = df_y[:len(train)-2]\n",
    "test_x = df_x[len(train)-2:]\n",
    "\n",
    "train_x, valid_x, train_y, valid_y = train_test_split(x, y, test_size=0.2, random_state=42)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## lightgbm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score='raise',\n",
       "       estimator=LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\n",
       "       importance_type='split', learning_rate=0.01, max_depth=-1,\n",
       "       min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,\n",
       "       n_estimators=5000, n_jobs=-1, num_leaves=31, objective='regression',\n",
       "       random_state=None, reg_alpha=0.0, reg_lambda=0.0, silent=True,\n",
       "       subsample=1.0, subsample_for_bin=200000, subsample_freq=0,\n",
       "       verbose=-1),\n",
       "       fit_params={}, iid=True, n_jobs=-1,\n",
       "       param_grid={'max_depth': [4], 'num_leaves': [3], 'feature_fraction': [0.2], 'cat_smooth': [0], 'bagging_fraction': [0.9], 'bagging_freq': [3]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, scoring=None, verbose=0)"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "paramaters = {\n",
    "    'max_depth':[4],\n",
    "    'num_leaves':[3],\n",
    "    'feature_fraction': [0.2],\n",
    "    'cat_smooth': [1],\n",
    "    'bagging_fraction':[0.9],\n",
    "    'bagging_freq': [3],\n",
    "    'cat_smooth':[0]\n",
    "    \n",
    "}\n",
    "\n",
    "gbm = lgb.LGBMRegressor(\n",
    "                    objective='regression',\n",
    "                    learning_rate = 0.01,\n",
    "                    n_estimators=5000,\n",
    "                    verbose = -1\n",
    ")\n",
    "\n",
    "gscv = GridSearchCV(gbm,\n",
    "                    param_grid=paramaters,\n",
    "                    cv=5,\n",
    "                    n_jobs=-1\n",
    "                   )\n",
    "gscv.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'bagging_fraction': 0.9,\n",
       " 'bagging_freq': 3,\n",
       " 'cat_smooth': 0,\n",
       " 'feature_fraction': 0.2,\n",
       " 'max_depth': 4,\n",
       " 'num_leaves': 3}"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gscv.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9112199443806296"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gscv.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.08705014158898404"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(np.sum(np.power((gscv.best_estimator_.predict(valid_x) - valid_y),2))/len(valid_y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## xgboost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Voyager\\Anaconda3\\lib\\site-packages\\xgboost\\core.py:587: FutureWarning: Series.base is deprecated and will be removed in a future version\n",
      "  if getattr(data, 'base', None) is not None and \\\n",
      "C:\\Users\\Voyager\\Anaconda3\\lib\\site-packages\\xgboost\\core.py:588: FutureWarning: Series.base is deprecated and will be removed in a future version\n",
      "  data.base is not None and isinstance(data, np.ndarray) \\\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score='raise',\n",
       "       estimator=XGBRegressor(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
       "       colsample_bynode=1, colsample_bytree=0.7, gamma=0,\n",
       "       importance_type='gain', learning_rate=0.01, max_delta_step=0,\n",
       "       max_depth=3, min_child_weight=0, missing=None, n_estimators=3460,\n",
       "       n_jobs=1, nthread=-1, objective='reg:squarederror', random_state=42,\n",
       "       reg_alpha=6e-05, reg_lambda=1, scale_pos_weight=1, seed=27,\n",
       "       silent=None, subsample=0.7, verbosity=1),\n",
       "       fit_params={}, iid=True, n_jobs=-1, param_grid={'max_depth': [3]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, scoring=None, verbose=0)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = {\n",
    "    'max_depth': [3]\n",
    "}\n",
    "xgboost = XGBRegressor(learning_rate=0.01,\n",
    "                       n_estimators=3460,\n",
    "                       min_child_weight=0,\n",
    "                       gamma = 0,\n",
    "                       subsample=0.7,\n",
    "                       colsample_bytree=0.7,\n",
    "                       objective='reg:squarederror',\n",
    "                       nthread=-1,\n",
    "                       scale_pos_weight=1,\n",
    "                       seed=27,\n",
    "                       reg_alpha=0.00006,\n",
    "                       random_state=42)\n",
    "gscv_xg = GridSearchCV(xgboost,\n",
    "                       cv=5,\n",
    "                       param_grid=params,\n",
    "                       n_jobs=-1)\n",
    "gscv_xg.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.9182838939823688"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gscv_xg.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.051259672596635816"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(np.sum(np.power((gscv_xg.best_estimator_.predict(valid_x) - valid_y),2))/len(valid_y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## svr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score='raise',\n",
       "       estimator=SVR(C=20, cache_size=200, coef0=0.0, degree=3, epsilon=0.1, gamma='auto',\n",
       "  kernel='rbf', max_iter=-1, shrinking=True, tol=0.001, verbose=False),\n",
       "       fit_params={}, iid=True, n_jobs=-1,\n",
       "       param_grid={'epsilon': [0.001], 'gamma': [0.0001]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, scoring=None, verbose=0)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = {\n",
    "    'epsilon' : [0.001],\n",
    "    'gamma' : [0.0001]\n",
    "}\n",
    "svr = SVR(C=20)\n",
    "gscv_svr = GridSearchCV(svr,\n",
    "                        cv=5,\n",
    "                       param_grid = params,\n",
    "                       n_jobs = -1)\n",
    "gscv_svr.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.1262860091578182"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gscv_svr.best_score_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'epsilon': 0.001, 'gamma': 0.0001}"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gscv_svr.best_params_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0015414986235854351"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(np.sum(np.power((gscv_svr.best_estimator_.predict(valid_x) - valid_y),2))/len(valid_y))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lasso"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=3, error_score='raise',\n",
       "       estimator=Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=100000.0,\n",
       "   normalize=False, positive=False, precompute=False, random_state=42,\n",
       "   selection='cyclic', tol=0.0001, warm_start=False),\n",
       "       fit_params={}, iid=True, n_jobs=-1,\n",
       "       param_grid={'alpha': [0.0001, 0.0003, 0.001]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, scoring=None, verbose=0)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "params = {\n",
    "    'alpha': [0.001] \n",
    "}\n",
    "lasso = Lasso(max_iter=1e5,\n",
    "             random_state=42)\n",
    "gscv_lasso = GridSearchCV(lasso,\n",
    "                          cv=3,\n",
    "                         param_grid = params,\n",
    "                         n_jobs = -1)\n",
    "gscv_lasso.fit(x, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Best score:  0.9172391240976264\n",
      "Best params:  {'alpha': 0.001}\n"
     ]
    }
   ],
   "source": [
    "print('Best score: ', gscv_lasso.best_score_)\n",
    "print('Best params: ', gscv_lasso.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.10113173725356718"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(np.sum(np.power((gscv_lasso.best_estimator_.predict(valid_x) - valid_y),2))/len(valid_y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred_lgb = gscv.best_estimator_.predict(test_x)\n",
    "pred_xg = gscv_xg.best_estimator_.predict(test_x)\n",
    "pred_svr = gscv.best_estimator_.predict(test_x)\n",
    "pred_lasso = gscv.best_estimator_.predict(test_x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "pred = pred_lasso\n",
    "\n",
    "submission = pd.DataFrame({'Id':test.Id, 'SalePrice':np.expm1(pred)})\n",
    "submission.to_csv('submission_2020_02_19.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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